title: [Generalization of the Brown-Forsythe approach to factorial designs].
abstract: The current paper proposes a solution that generalizes ideas of Brown and Forsythe to the problem of comparing hypotheses in two-way classification designs with heteroscedastic error structure. Unlike the standard analysis of variance, the proposed approach does not require the homogeneity assumption. A comprehensive simulation study, in which sample size of the cells, relationship between the cell sizes and unequal variance, degree of variance heterogeneity, and population distribution shape were systematically manipulated, shows that the proposed approximation was generally robust when normality and heterogeneity were jointly violated.
authors.affiliation: Facultad de Psicología, Universidad de Oviedo, Oviedo, Spain. gvallejo@uniovi.es
authors.forename: Guillermo
authors.initials: G
authors.lastname: Vallejo Seco
authors.forename: María Paula
authors.initials: MP
authors.lastname: Fernández García
authors.forename: Pablo Esteban
authors.initials: PE
authors.lastname: Livacic Rojas
mesh_terms: D005163:Factor Analysis, Statistical; D006801:Humans; D008960:Models, Psychological; D011584:Psychology / Q000379:methods / Q000706:statistics & numerical data; D011795:Surveys and Questionnaires